{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import string\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "tbpath = \"../../fits/\"\n",
    "productpath = \"../../postfit_derivatives/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "models = [\"fulllinearmodel_fit_table.csv\",\"reducedlinearmodelNegBinom_fit_table.csv\",\n",
    "          \"nonlinearmodel_fit_table.csv\"]\n",
    "# model_hash = {}\n",
    "# k = -1\n",
    "# for model in models:\n",
    "#     k += 1\n",
    "#     model_hash[model] = string.ascii_uppercase[k]\n",
    "\n",
    "# df = pd.DataFrame.from_dict(model_hash, orient='index')\n",
    "# df.to_csv('../postmodel_derivatives/model_hash.csv', header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rois = []\n",
    "for model in models:\n",
    "    df = pd.read_csv(tbpath + model) #get rois in all tables (some may have failed)\n",
    "    rois += list(df.roi.unique())\n",
    "\n",
    "    \n",
    "rois = list(set(rois))\n",
    "roi_us = np.sort([i for i in rois if i[:2]=='US'])[::-1]\n",
    "roi_other = np.sort([i for i in rois if i[:2]!='US'])[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "theta = \"q\"\n",
    "df2 = pd.DataFrame(columns=[i.split('_fit_table.csv')[0] for i in models])\n",
    "k = 0\n",
    "for roi in rois:\n",
    "#     print(roi)\n",
    "    x = []\n",
    "    for model in models:\n",
    "        df = pd.read_csv(tbpath + model)\n",
    "        try:\n",
    "            x.append(df.loc[(df.roi==roi)&(df['quantile']==0.5), theta].values[0])\n",
    "        except:\n",
    "            print()\n",
    "    if len(x)==len(models):\n",
    "        k += 1\n",
    "#         print(x)\n",
    "        df2.loc[k] = x "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f = sns.pairplot(df2)\n",
    "f.fig.suptitle(theta, fontsize=18)\n",
    "plt.subplots_adjust(left=0.1, bottom=0.1)\n",
    "plt.savefig(productpath + 'pairsplot_'+theta+'.png')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
